A two-stage partial fixing approach for solving the residency block scheduling problem.

Area of Science:

• Operations Research
• Medical Education
• Healthcare Management

Background:

• Medical residency programs face complex scheduling challenges.
• Balancing hospital coverage and resident training is crucial.
• Traditional scheduling methods are often computationally intensive.

Purpose of the Study:

• To develop an efficient algorithm for constructing feasible annual block schedules for medical residents.
• To address the combinatorial optimization problem of resident scheduling.
• To improve upon the performance of traditional scheduling techniques.

Main Methods:

• A two-stage partial fixing approach for schedule construction.
• Utilizing problem relaxation in the first stage for resident assignments.
• Employing cut generation mechanisms and a network-based model for optimization.
• Iterative completion of the schedule based on fixed assignments.

Main Results:

• The proposed approach significantly speeds up schedule construction (at least 5x, over 100x for large instances).
• Achieved faster and more robust performance compared to direct application of traditional methods.
• Successfully generated feasible annual block schedules meeting all requirements.

Conclusions:

• The novel two-stage iterative approach offers a substantial performance improvement for resident block scheduling.
• This method effectively balances complex coverage and education requirements.
• The findings have practical implications for optimizing medical training program logistics.